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LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism.

BMC bioinformatics

Dromms RA, Lee JY, Styczynski MP.
PMID: 32122331
BMC Bioinformatics. 2020 Mar 02;21(1):93. doi: 10.1186/s12859-020-3422-0.

BACKGROUND: The systems-scale analysis of cellular metabolites, "metabolomics," provides data ideal for applications in metabolic engineering. However, many of the computational tools for strain design are built around Flux Balance Analysis (FBA), which makes assumptions that preclude direct integration...

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Dromms RA, Lee JY, Styczynski MP. LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism. BMC Bioinformatics. 2020;21(1):93doi: 10.1186/s12859-020-3422-0.
Dromms, R. A., Lee, J. Y., & Styczynski, M. P. (2020). LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism. BMC bioinformatics, 21(1), 93. https://doi.org/10.1186/s12859-020-3422-0
Dromms, Robert A, et al. "LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism." BMC bioinformatics vol. 21,1 (2020): 93. doi: https://doi.org/10.1186/s12859-020-3422-0
Dromms RA, Lee JY, Styczynski MP. LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism. BMC Bioinformatics. 2020 Mar 02;21(1):93. doi: 10.1186/s12859-020-3422-0. PMID: 32122331; PMCID: PMC7053146.
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